Live snapshot
Cost-Optimised Data Stack ✓
From raw data to decisions in weeks, not months.
We design modern data platforms that your finance, ops, and product teams
can actually use—without blowing up your Snowflake or Fabric bill.
Data Engineering
BI Dashboards
Cloud Cost Optimisation
AI / AutoInsights
Cloud spend vs. value
40–60% optimisation window detected
Pipeline health
99.3% successful runs · last 30 days
AI
Modern data engineering partner for cost-sensitive teams
Build a future-ready data stack
without a future-shocking bill.
At Cubegle Technologies, we combine Data Engineering, BI, and AI/ML to turn messy, scattered data into reliable dashboards, governed data models, and low-maintenance pipelines—optimised for cost, speed, and clarity.
13+ years in Data
500+ dashboards · 200+ pipelines · multi-cloud experience (Azure / AWS)
13+ yrs
Data Engineering & BI experience
40–60%
Typical reduction in ETL & warehouse costs
500+
Dashboards delivered across domains
Services
What we build for you
From raw data to trusted insights: we cover the full
stack—data ingestion, warehousing, modelling, dashboards, and AI-driven analytics.
Data Engineering
Design and implement reliable ETL/ELT pipelines that move data from your apps,
databases, and APIs into a single, analytics-ready layer.
Pentaho PDI
ADF / Glue
Airflow
SQL / Python
Modern Data Warehouse
Robust modelling and storage on cloud or hybrid: star schemas, SCD, partitioning,
incremental loads, and performance-tuned queries.
Azure SQL / Synapse
AWS RDS / Redshift
Snowflake
MySQL / Postgres
BI Dashboards & Reporting
Pixel-perfect dashboards for leadership and operations—with row-level security,
governed datasets, and refresh-aware design.
Power BI
Tableau
Pentaho BA
Superset / Metabase
Cloud & DevOps for Data
Infrastructure-as-code, CI/CD, environment strategy, and observability so your data
stack is secure, scalable, and easy to maintain.
Azure
AWS
GCP
Jenkins / GitHub Actions
AI / ML & AutoInsights
Build ML-ready datasets, integrate models, and plug in our AutoInsights-style
accelerators for anomaly detection, forecasts, and alerting.
Python
Notebook pipelines
ML-ready feature store
Advisory & Audits
Architecture reviews, cost audits, and roadmap consulting if you already have a
partial data setup and need a second pair of eyes.
Health check
Migration strategy
Cost vs. value mapping
Engagement models
How we typically work with clients
Whether you’re validating a product, cleaning up legacy BI, or building a full data
platform from scratch, we adapt to your stage and budget.
For startups & new products
Launch-Ready Analytics Starter
A focused 4–6 week sprint to get your first end-to-end pipeline and executive dashboard live.
1–2 key dashboards
Single source integration
Cloud-cost friendly
For growing teams
Data Platform Modernisation
Migrate or refactor existing ETL/BI into a modern, governed, and maintainable architecture.
Cost optimisation (40–60%)
Best-practice modelling
Observability & alerting
For long-term outcomes
Embedded Data Team
A dedicated Cubegle pod (Data Engineer + BI + Architect) embedded with your product or ops team.
Monthly retainer
Flexible scope
Enterprise-grade practices
Industries
Domains we understand deeply
We’ve worked with a mix of startups and established companies across operations-heavy
and data-rich industries.
Hospitality & Food Waste
Kitchen operations, inventory, and waste analytics—closing the loop between data,
operations, and sustainability metrics.
Recipe & menu analytics
Ops dashboards
Healthcare & Life Sciences
Regulatory-aware reporting, patient journey analytics, and operations dashboards with
strict data governance.
Patient flow
Utilisation KPIs
Retail, SaaS & B2B
Sales funnels, subscriptions, cohorts, and revenue analytics for recurring-revenue
and B2B businesses.
Sales & pipeline
MRR / churn
Process
How a typical engagement flows
No big-bang rewrites. We prefer small, high-impact milestones that keep stakeholders
confident and systems stable.
1
Discovery & audit
Understand business goals, current stack, data quality, and reporting pain points.
2
Architecture & roadmap
Propose a future-ready, cost-aware design with a phased implementation plan.
3
Implementation & handover
Build pipelines, models, and dashboards with documentation and knowledge transfer.
4
Optimise & scale
Tune performance, trim costs, and gradually expand to more use cases and teams.
Case studies
Results our clients care about
Names and details can be anonymised publicly, but the impact is real: cost savings,
faster reporting, and fewer late-night pipeline fixes.
Food-tech / Hospitality
Unified kitchen analytics across regions
Consolidated multiple data sources (POS, inventory, waste tracking) into a single
warehouse powering executive and ops dashboards.
40% reduction in manual Excel work
Daily automated refresh
SaaS B2B
Subscription & revenue 360° visibility
Built a metric-driven data model and Power BI layer that surfaces revenue KPIs,
churn, and cohorts for GTM and leadership teams.
Under 5 sec dashboard loads
Single source of truth
Multi-cloud migration
Data platform modernisation & cost control
Refactored legacy ETL and warehouse jobs to a modern stack with observability and
cost-aware design patterns.
40–60% lower monthly spend
99%+ pipeline reliability
Tech stack
Tools we are comfortable owning
We’re pragmatic and vendor-neutral: we’ll use what you already have, recommend where
upgrades are needed, and avoid unnecessary complexity.
Cloud & Storage
Azure
AWS
GCP
Azure SQL / Synapse
S3 / ADLS
Warehousing & Databases
Snowflake
Redshift
BigQuery
SQL Server
MySQL / Aurora
PostgreSQL
Pipelines & Orchestration
Pentaho PDI
Azure Data Factory
AWS Glue
Airflow
dbt (where relevant)
BI & Visualisation
Power BI
Tableau
Pentaho BA Server
Superset
Metabase
Engineering & AI
Python
SQL
Pandas / PySpark
Kafka (streams)
Notebooks (ML)
DevOps & Governance
Git / GitHub / GitLab
Jenkins / CI
RBAC & RLS patterns
Monitoring & alerts
About
Who is behind Cubegle
We’re a lean, hands-on team of data engineers and BI specialists who prefer
long-term partnerships over one-off dashboards.
Cubegle Technologies was founded by senior data professionals with experience in BI, Data Engineering, and analytics. We’ve worked with fast-moving startups and enterprise teams to design data platforms that support real-world decision-making—without over-engineering or overspending.
Our philosophy is simple: build only what the business can use, use cloud where it truly adds value, and leave behind a system that future teams will thank you for.
Owned end-to-end data projects across domains
Comfortable with both legacy & modern stacks
Remote-friendly, documentation-heavy, transparent
“Cubegle quickly understood our messy reality and gave us a clean, reliable
reporting layer. Our leadership now trusts the numbers—and our teams spend far
less time firefighting data issues.”
“We brought Cubegle in for Power BI dashboards; they ended up fixing our data
model, warehouse, and refresh strategy as well. The difference in reliability
and performance is night and day.”
Contact
Let’s talk about your data stack
Share a quick overview of your current setup and goals—we’ll respond with
a few concrete options and a possible starting engagement.
Book a free consult
Tell us a bit about your data environment, and we’ll schedule a 30–45 minute conversation to explore fit, architecture options, and timelines.
What to prepare before our call
- • Systems in play – CRMs, apps, databases, data tools you already use.
- • Top 3 reports you wish were automated and reliable.
- • Rough cloud / tool spend if available (for cost-optimisation ideas).
- • Any constraints around security, compliance, or hosting.
Based in India · Working with clients across time zones.